Plotting Error - EEG Unit

Support & Discussions
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1

Hello,

This is a sample of my dataset.

image
image1202×171 10.3 KB

sampling frequency - 128 Hz

  • operating system: Windows 10

When plotted getting an distorted image like the below one. How to rectify it and get a proper signal.
raw.plot()

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In the csv folder of the dataset I have events also. Have created a channel for the events also. But getting error.
ValueError: No stim channels found. Consider specifying them manually using the ‘stim_channel’ parameter.

events = mne.find_events(raw)

How to process the events col. of the csv file and process the eeg signals and predict which event based on the 14 channels?

Thanks

2

Hello,

the data values seem to be in µV, but MNE requires SI units, i.e., Volts. Multiply the values by 1e-6 and things should already look much better.

As for the other question, can you please open a separate topic?

Best wishes,
Richard

3

Hello Richard,

dataframe = pd.read_csv('eeg.csv') 
eeg_data = dataframe.transpose().to_numpy()
n_channels = len(dataframe.columns)    
sampling_freq = 128  
info = mne.create_info(n_channels, sfreq=sampling_freq)

info = mne.create_info(ch_names, ch_types=ch_types, sfreq=sampling_freq)
info.set_montage('standard_1020')

raw = mne.io.RawArray(eeg_data, info)
raw.save('eeg.fif',overwrite=True)

raw.plot()

I’m converting it from .csv to .fif and plotting, so then how do I convert the data unit from µV to V.

Thanks

4

Just multiply the dataframe by 1e-6 before creating the RawArray, that should do the trick.

Best wishes
Richard

6

Hello @Star, great to see it’s working!

Can you please post your other question into a new topic? Thank you!

Richard

7

Thanks, Have posted it separately.

8

Sorry but now the event column in the data frame also gets multiplied with 1e-6. That why I asked the Event’s based classification question (Event's based Classification) with this also.
Could you help me with this @richard .

Thanks

9

You can exclude the last column from the multiplication by doing something like:

dataframe.loc[
    :,  # all rows
    dataframe.columns[:-1]  # omit last column (events)
] *= 1e-6

Best wishes,
Richard